The present invention relates to the document processing system art. It finds particular application in conjunction with image segmentation, and more particularly a method for augmenting sum-of-laplacians in light and dark areas of halftone field to maintain reliable image segmentation. However, it should be appreciated that the present invention may also find application in conjunction with other types of digital imaging systems and applications that discern how an image was rendered.
Document processing systems often need to take an image representation with a low level of organizational structure, such as a simple bit or byte per pixel rectangular video map, and infer structure to guide further processing or analysis of the image. For example, in a reprographic system a document is optically scanned and the reflectance of each pixel is converted to an 8 bit digital value, forming an 8 bit per pixel matrix of integers representing the original document. Various image processing is then performed to enhance the image and convert it to a different resolution and form which can be rendered by a particular marking technology, such as a bi-level Xerographic printer. The purpose of the processing is to produce an output copy which appears to the human eye to be equal to or in some sense better than the original. Unfortunately, the appropriate image processing is different for different types of input documents, typical broad classes being text, continuous tone, and halftones of various techniques and frequencies.
Furthermore, many user originals contain more than one document type in different areas of the page, for example a magazine article with inset halftoned photographs, or text embedded in a tinted background. This explains the need to classify each document pixel, so that appropriate processing can be performed. In other applications, the pixel classification determined may be simply communicated to a subsequent process which analyzes the pixel level classification map further.
Algorithms for classifying image pixels according to document type (e.g. text, contone, halftone) make their decision based on image context in the vicinity of the pixel being classified. In the case of a halftoned document type, one of the most reliable microclassifiers used to detect the presence of a halftone is the absolute value of the sum of the laplacians in a small area surrounding the pixel being classified (abbreviated Sij). Unfortunately, Sij diminishes in light and dark regions, resulting in non-detection of halftone, and subsequent incorrect choice of image processing and rendering. This results in moire and artifacts due to inappropriate switching between rendering schemes on the output document.
Historically, Sij is calculated in the same way over an entire image, independent of video content, and factored into the halftone detection algorithm. In general, Sij values are very large for halftone areas of an image compared to contone areas, meaning that there is large latitude in how Sij is utilized by a detection algorithm. The exception to this generalization is that Sij diminishes in light and dark regions, resulting in non-detection of halftone, and subsequent incorrect choice of image processing and rendering.
In the past these defects were not visible because the use of hysteresis or other state-based methods, and rectangular segmentation blocks over which statistics were accumulated suppressed such errors, as did rendering TRCs designed to hide shortfalls not only in segmentation but in other parts of the system as well, such as the scanner. This was especially true in the dark areas of an image, where small errors in the video from the scanner are easily visible.
Recent advances in scanner technology and image segmentation, driven by the desire to more faithfully reproduce the original image, have eliminated the state based methods and the use of rectangular segmentation blocks. TRCs no longer saturate in the dark and light areas to hide flaws in the system, but are designed to faithfully render the original document at all densities. The new segmentation schemes, while avoiding the generation of rectangular artifacts, classify each pixel independently, precluding the possibility of neighborhood classification statistics overriding a given pixel's erroneous classification and thereby hiding errors.
To understand why Sij diminishes in dark and light areas of an image, it is observed that a halftone pattern is comprised of a matrix of halftone cells with each cell having either a white or black background (depending on whether it is greater or less than about 50% reflectance) and a round dot of the opposite color in the middle. Each individual 3.times.3 laplacian will be zero over a uniform field, and large when straddling an edge, such as the edge of the halftone dot. Therefore, an areal sum of the laplacians over a few halftone cells would be expected to be roughly proportional to the total halftone dot edge length, that is the sum of the circumferences of the halftone dots. This is borne out by plotting Sij versus reflectance for different halftone frequencies, and noting that the plots are very similar regardless of halftone frequency. An exemplary Sij versus reflectance plot for a 65 LPI halftone screen frequency is shown in FIG. 1. The reflectance is represented as a video gray level with 0 indicating zero reflectance or white, and 255 indicating 100% reflectance or black.
Previously, an Sij threshold of about 170 was successfully used to classify image areas as halftone. Looking at FIG. 1, it is easy to see why this produced satisfactory results, except in the very lightest and darkest areas. Sij is almost universally greater than 170, regardless of average density or halftone frequency. Sijs over plain white paper or contone images are typically in the range of 90-130, leaving a comfortable separation between halftone and contone or background areas of an image. However, a diminished Sij in light and dark regions results in non-detection of halftone fields, and subsequent incorrect choice of image processing and rendering.
Accordingly, it has been considered desirable to develop a new and improved method for augmenting sum-of-laplacians in light and dark areas of halftone fields to maintain reliable segmentation which meets the above-stated needs and overcomes the foregoing difficulties and others while providing better and more advantageous results.